Pain is multifactorial in origin with both genetic and environmental factors contributing to individual variations. Candidate gene studies on the basis of biological hypotheses have been performed to identify relevant genetic variation in complex traits such as pain. However, the complicated mesh of contributing factors and the thousands of molecules involved in different pain phenotypes makes it difficult to detect responsible genetic variations for an individuals unique susceptibility to pain. It is unlikely that common variations in a single gene act dominantly on pain;rather, the contribution of each gene seems to be subtle, acting on one of multiple pain pathways, making its signal difficult to detect. Even though pain has been one of the most significant and frequent problems affecting quality of life for thousands of years, analgesic therapy is still largely limited to opioids and aspirin-like drugs, with the limitations of these drug classes. The combined impact of the rapid increase in knowledge of diseases and the ability to apply powerful and high capacity technology has raised expectations for more effective and safer medicines for pain management. Developing new treatment strategies for the pain management is also critically dependent on identifying new target molecules and defining pain phenotypes for specific types of pain. Therefore the first step of this project has been to define the characteristics of experimental and clinical pain phenotypes. Contributing factors such as gender, ethnicity and psychological factors predominate over the role of genetic factors in pain and analgesic responses when evaluating groups of patients (Kim et al. 2004a;Kim et al. 2004b). But genetic variability may be important at the level of the individual (Dionne et al. 2005). Based on this project, we found haploblocks from candidate pain genes for each major ethnic population. Human haplotype data of pain related genes provide basic information for the genetic association studies of pain sensitivity and responses to analgesics. We also applied this haplotype data to find the association with experimental pain sensitivity and verified that this method is useful in investigating the role of genetics in pain sensitivity (Kim et al. 2006, JMG). We also have performed individual SNP association studies of candidate genes and reported results contrary to previous published studies, which may have been biased with population stratification and small sample size (Kim et al. 2006, Molecular Pain). Meanwhile we investigated the influence of the genetic variations in prostaglandin synthesis on the clinically induced pain and analgesic responses in the oral surgery model. From this, we found that homozygous G/G patients of SNP in the promoter region (-765) of COX-2 gene showed significantly different responses to common analgesic drugs compared to G/C heterozygous and C/C homozygous patients (Lee et al. 2006, CPT). We recently published a whole genome scan study related to clinical pain sensitivity using 500,000 SNPs assay in the oral surgery model. Based on whole genome scale investigation, we have further characterized a candidate region with dense genotyping and identified a genetic locus in a zinc finger protein that contributes to interindividual variability in analgesic drug responses following minor surgery. We have expanded the number of testing SNPs up to 1 million from human genome and are genotyping hundreds of patients with fibromyalgia, acute coronary syndrome and subarrachnoid hemorrhage. Detailed information and functional genomic studies of the candidate regions from those projects may provide knowledge for the genetic role in responses to tissue injury, pain and analgesia on an individual patient basis. Recently, we launched projects with next generation sequencing technology, which allows us perform entire genome sequencing for individuals with unique phenotypes such as capsaicin non-sensitive patients, and epigenetic changes following long term environmental changes such as soldiers exposed to combat and traumatic brain injury. The role of genetic and epigenetic factors on clinical pain will continue to be studied in acute pain using genotyping, gene and protein expression, and patient reported outcomes to better understand the reciprocal interplay between these factors and the inflammatory cascade. These data will be analyzed with whole genome scan, microarray, ELISA, SNP genotyping, whole genome sequencing and real time PCR. From these results along with biological knowledge of pain pathways, we will be able to suggest molecular-genetic mechanisms of pain and analgesia at the level of the individual, suggest new targets for analgesic drugs and test the efficacy and adverse reactions of newly developed or currently used drugs.